The operations of mobile platforms are typically facilitated by obtaining position information of objects in a surrounding environment, using a combination of sensors. The information obtained regarding the positions of objects can facilitate the detecting pedestrians and/or vehicles in the environment, thereby allowing the mobile platforms to avoid obstacles during navigation. Typical optical detection sensors, such as monocular cameras, can detect an object based on computer vision and machine learning algorithms, but cannot consistently provide three-dimensional position information of the target. Emitter/detector sensors, such as LiDAR sensors, typically transmit a pulsed signal (e.g. laser signal) outwards, detect the pulsed signal reflections, and measure three-dimensional information (e.g., laser scanning points) in the environment to facilitate mapping the environment. Typical emitter/detector sensors can provide three-dimensional geometry information of the environment, but object detection based thereon is relatively difficult. Additionally, conventional omni-directional laser sensors with 360-degree horizontal field of view (FOV) can be expensive and non-customizable. Accordingly, there remains a need for improved sensing techniques and devices for mobile platforms.